5.2 KiB
Mycelium GPU for Developers
The Energy Behind Intelligence
Overview
Mycelium GPU provides unified access to distributed GPU acceleration across the ThreeFold Grid. It transforms fragmented GPU resources into a single sovereign fabric for running AI, ML, and rendering workloads.
Core Concept
Mycelium GPU unifies distributed acceleration into a single sovereign fabric — turning fragmented hardware into one adaptive intelligence layer. Run AI, ML, and rendering workloads anywhere, from edge to core, with deterministic performance and transparent cost.
Key Principles
- No Silos: All GPU resources accessible through single interface
- No Intermediaries: Direct access to GPU resources
- Raw, Verifiable Power: Every GPU cycle cryptographically verified
- Orchestrated Through Code: GPU resources managed through APIs and smart contracts
Use Cases
AI/ML Training
Run GPU-accelerated workloads for deep learning and data science on demand.
Features:
- GPU Acceleration: High-performance computing for machine learning
- Scalable Compute: Scale training across multiple GPU resources
- Cost Optimization: Pay only for actual GPU usage
Rendering & Visualization
Run high-performance graphics processing workloads.
Applications:
- 3D Rendering: Distributed rendering for film, games, and architecture
- Scientific Visualization: Complex data visualization and analysis
- Virtual Reality: Real-time VR/AR processing
- Digital Twins: Real-time simulation and modeling
General GPU Computing
High-performance computing for various computational workloads.
Applications:
- Scientific Simulations: Physics, chemistry, climate modeling
- Financial Modeling: Risk analysis and algorithmic trading
- Cryptocurrency: Mining and blockchain processing
- Protein Folding: Drug discovery and molecular modeling
Integration with Mycelium Cloud
Mycelium GPU works seamlessly with Mycelium Cloud infrastructure:
- Unified Networking: GPU nodes accessible via Mycelium network
- Shared Security: Zero-trust security model applies to GPU operations
- Storage Integration: Access quantum-safe storage from GPU workloads
- Kubernetes Support: GPU workloads can be deployed as Kubernetes resources
Deployment Example
# GPU workload specification for Kubernetes
apiVersion: apps/v1
kind: Deployment
metadata:
name: gpu-workload
spec:
replicas: 1
selector:
matchLabels:
app: gpu-compute
template:
metadata:
labels:
app: gpu-compute
spec:
containers:
- name: gpu-compute
image: tensorflow/tensorflow:latest-gpu
resources:
limits:
nvidia.com/gpu: 1
env:
- name: MYCELIUM_GPU_REGION
value: "auto"
Getting Started
Access GPU Resources
- Account Setup: Create Mycelium account with GPU access
- Resource Request: Use Mycelium GPU APIs to request GPU resources
- Workload Deployment: Deploy your AI/ML or compute workload
- Monitor Usage: Track GPU utilization and costs through dashboard
Basic Workflow
Application → Mycelium GPU API → GPU Resource Allocation → Workload Execution
Key Benefits
- Deterministic Performance: Predictable GPU allocation and performance
- Global Distribution: Access GPU resources worldwide
- Transparent Costs: Clear pricing without hidden fees
- Sovereign Control: Full control over GPU workloads and data
Technical Architecture
Distributed GPU Mesh
Mycelium GPU creates a peer-to-peer network of GPU resources accessible through the Mycelium Network.
Components:
- GPU Nodes: Physical GPU hardware distributed globally
- Mycelium Network: Encrypted peer-to-peer communication layer
- Orchestration Layer: API and smart contract-based resource management
- Monitoring: Real-time GPU utilization and health monitoring
Performance Characteristics
- Edge-to-Core Deployment: Run workloads from edge devices to data centers
- Adaptive Intelligence Layer: Optimizes GPU resource allocation
- Deterministic Performance: Guaranteed resource availability and performance
- Transparent Cost: All GPU usage tracked and billed transparently
Key Differentiators
Unified Fabric
Transforms fragmented GPU resources into a single, unified acceleration fabric accessible through standard APIs.
Sovereign Control
Complete control over GPU workloads with no vendor lock-in or geographical restrictions.
Code-Driven Orchestration
GPU resources managed through APIs and smart contracts, enabling automated and verifiable resource allocation.
Deterministic Performance
Guaranteed GPU allocation with consistent performance characteristics across all workloads.
Cost Efficiency
Mycelium GPU provides cost-effective access to GPU resources through:
- Transparent Pricing: No hidden fees or surprise charges
- Pay-per-Usage: Pay only for actual GPU consumption
- Global Optimization: Access GPUs where they're most cost-effective
- No Vendor Lock-in: Avoid premium pricing from single providers
Mycelium GPU - Unifying distributed acceleration into a sovereign fabric.